For the past 30 years, Melanoma incidence rates have been increasingly high. Though most people diagnosed with skin cancer have higher chances to cure, Melanoma survival rates are lower than non-Melanoma skin cancer. As more new cases of skin cancer are being diagnosed in the U.S. each year, a system to prevent this type of skin cancer is being awaited and is highly in-demand. Unprotected exposure to UV radiation and consuming certain foods are considered to be the most important risk factors for skin cancer. In this paper, we propose a novel smart-phone based virtual reality system to aid in the skin cancer prevention and pain treatment. Our proposed system consists of two stages, prevention stage and treatment stage. In the prevention stage, we capture user environmental data (i.e. UV radiation level and image of foods) and plug it into the system to alert the user at real-time to prevent risks associated with developing the skin cancer disease. In this stage, we present an image food recognition technique, where the user will be able to capture images of different food items, and our system will analyze/process the images and alert the user at real-time to avoid consuming certain types of food if it belongs to the dangerous and/or risky list. The idea here is to introduce a fast, convenient and efficient food classification method to alert the user if the food item (whose image has been captured) is harmful. This work introduces convenient steps for automating the process of food item identification and differentiation from the background image. Experimental results on a number of food images confirms the efficiency of our technique. In the second stage, different techniques will be introduced to aid in the treatment of skin cancer pain. In this paper, however, we only focus on image processing techniques for identifying/classifying the food item in the prevention stage, and the complete system implementation is left as our future plan.
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